I'm using python's sklearn for multi-class classification (SVC) When using the predict method, i get very high scores with my dataset, However, I want to plot ROC curves for each of my classes. That is, I would like to reduce the problem to a in_class/out_of_class problem for each of the classes. For that i resorted to the predict_proba method of the SVC. However, I find no correlation between the probabilities given and the predictions. For instance, for a 5 class classification problem, I may get a prediction of the 1st class, but get a probability vector - [ 0.1, 0.2, 0.5, 0.3, 0.0 ]. The 1st class did not get the highest probability.
Does anyone know how the SVM uses its decision function to make a prediction, or how the predict_proba works on a multi-class problem?